Decreased electrocortical temporal complexity distinguishes sleep from wakefulness

Abstract

In most mammals, the sleep-wake cycle is constituted by three behavioral states: wakefulness (W), non-NREM (NREM) sleep, and REM sleep. These states are associated with drastic changes in cognitive capacities, mostly determined by the function of the thalamo-cortical system. The intra-cranial electroencephalogram or electocorticogram (ECoG), is an important tool for measuring the changes in the thalamo-cortical activity during W and sleep. In the present study we analyzed broad-band ECoG recordings of the rat by means of a time-series complexity measure that is easy to implement and robust to noise: the Permutation Entropy (PeEn). We found that PeEn is maximal during W and decreases during sleep. These results bring to light the different thalamo-cortical dynamics emerging during sleep-wake states, which are associated with the well-known spectral changes that occur when passing from W to sleep. Moreover, the PeEn analysis allows to determine behavioral states independently of the electrodes' cortical location, which points to an underlying global pattern in the signal that differs among the cycle states that is missed by classical methods. Consequently, our data suggest that PeEn analysis of a single EEG channel could allow for cheap, easy, and efficient sleep monitoring. 10/11

Transition of Neural Activity From the Chaotic Bipolar-Disorder State to the Periodic Healthy State Using External Feedback Signals

“…Furthermore, this effect might also contribute to a reduction in mixed states, hypomania, and autonomic hyperactivations that can occur in BD chronotherapy due to overapplication of light stimuli and medication. Additionally, methods for measuring the daily variation of frontal neural activity are now under development, with a focus on EEG approaches (Croce et al, 2018 ; González et al, 2019 ). These methods might contribute to the realization of a form of chronotherapy modulated by RRO feedback.…”

“…Second, we used competition between excitatory and inhibitory neurons in this study to describe long-term neural dynamics in the frontal cortex. However, the questions of what reflects the long-term dynamics of brain activity and what mechanism produces it are currently controversial (Croce et al, 2018 ; González et al, 2019 ). Therefore, it is important that our proposed method be verified with models based on other neural mechanisms for producing long-term neural dynamics in the frontal cortex.…”

Electrocortical temporal complexity during wakefulness and sleep: an updated account

“…In our previous work (2), we found that the ECoGs' temporal complexity decreased from wakefulness to sleep; i.e., the repertoire of dynamical motifs was reduced when the animals fell asleep ( Figure 1A, B and C). Interestingly, we observed this result in several cortical locations independent of its function (motor, olfactory, somatosensorial and visual), which suggested that the loss in temporal complexity was a global motif developed in the passage from W to sleep.…”

“…The animals were chronically implanted with electrodes to monitor the states of sleep and W. To record the ECoG, stainless steel screw electrodes were placed on the skull above motor (bilateral), somatosensory (bilateral), visual cortices (bilateral), the right olfactory bulb, and cerebellum, which was the reference electrode (see Fig. 1a and Table 2 in González et al 2019). A neck bipolar electrode was employed to record the EMG.…”

Power and coherence in the EEG of the rat: impact of behavioral states, cortical area, lateralization and light/dark phases

“…We employed surgical procedures similar to those used in our previous studies (Cavelli et al, 2018;Gonzalez et al, 2019;Mondino et al, 2019). The animals were chronically implanted with intracranial electrodes.…”